Gaze tracking technology, as a most innovative human-computer interaction, has advantages such as high accuracy, simple to use, good stability, little interference to users and the like. Therefore, the gaze tracking technology possesses a wide application prospect in several fields such as medical aided diagnosis, auxiliary equipment for the disabled, advertising and marketing analysis, daily human-computer interaction and the like. Besides, augmented reality is penetrating into people's life increasingly, and how to combine the gaze tracking technology with the augmented reality to establish the visualized augmented reality in real-time interaction has been a focus to which people more and more pay attention.
Augmented Reality (AR) is to augment the reality information in the real world around the user through a 3D registration technology, so as to reach a “seamless” integration between the information of the real world and the information of the virtual world, bringing the user surreal sense experience. In order to provide a simple, efficient and bidirectional interactive mode to an augmented reality system, a combination of the gaze tracking technology with the augmented reality can not only track a gaze direction of the user, acquire an interested region by the user in a scene, but also present a characteristic of the augmented reality system combining virtuality with reality, wherein through a human eye image captured by an infrared camera, the augmented reality system based on a headset display with a gaze tracking function tracks the gaze direction and performs operations such as gaze transferring view, playing music and opening a video, and it has a strong effect of the augmented reality with an important research significance and has attracted extensive attention in recent years.
A structure of a headset gaze tracking system has its particularity. When the human eyes gaze at an object in a space with the head moving randomly, relative positions and distances between the human eyes and the screen as well as the human eyes and the camera remain constant, and there's no need to take an effect of the head's movement on gaze point estimation into account. Thus, a design of the headset gaze tracking system provides a new concept for the research of the technical field of gaze tracking, converting from researching how to avoid the influence of the head's extensive movement during estimating a gaze point position, into researching how to track movement information of the human eyes more simply and accurately inside a small space of the headset system to acquire the gaze direction of the human eyes. To sum up, extracting the eye movement feature accurately under the near-infrared light which represents the gaze direction, and establishing a simple and efficient gaze mapping model have become two key missions in the research of the headset gaze tracking system.
As for the eye movement feature extraction, an extraction effect thereof should satisfy requirements for high accuracy and strong real-time performance. Inside the headset gaze tracking system, the camera is closed to the human eyes and the human eye image captured by it is clear, but an uneven illumination would lead to a difference of the human eye image in the clarity; besides, owing to an effect of a reflector in the system, the human eye image captured by the camera would produce a deformation, and when the eye balls rotate in a relatively large angle, part of the eye movement feature would be covered by the eyelid or eyelash, leading to an incomplete outline or a false outline. At present, an eye movement feature extraction algorithm mostly extracts a feature of the pupil and combines a light spot of corneal reflex or the inner and outer eye corners, to extract the eye movement feature that accurately represents the gaze direction. These algorithms are usually so complicated that the real-time performance of the eye movement feature extraction cannot be guaranteed. Therefore, it has become one of the technical difficulties of the headset gaze tracking system that how to extract the eye movement feature rapidly and accurately under the near-infrared light.
As for establishment of the gaze mapping model, an object thereof is to obtain the gaze point position by using the extracted eye movement feature. Inside the headset gaze tracking system, the position of the camera is fixed, relative to the position of the human eyes, and the head's movement would not make an influence on calculation of the gaze point. However, the user tends to expect to put on the headset easily and use it conveniently when using the system. In the present gaze mapping model, a 2D mapping model algorithm is so simple that there's no need to achieve position information of a system device and that of the user in advance, but a plurality of infrared light sources or several calibration points of a screen are often used to establish a 2D mapping formula; whereas a 3D mapping model algorithm is so complicated that a complicated stereo camera or several cameras are needed to collect the human eye image so as to achieve a mapping relation of a 3D center of eyes and the gaze point of the screen, so that a hardware of the entire gaze tracking system is complicated. Thus, it has become a major technical difficulty existing in the headset gaze tracking system that how to guarantee the high accuracy of the gaze point estimation and meanwhile only a single camera and a single infrared light source are used to establish a simple gaze mapping model during calibration.